def _create_plot_component():
# Create a GridContainer to hold all of our plots
container = GridContainer(padding=20, fill_padding=True,
bgcolor="lightgray", use_backbuffer=True,
shape=(3,3), spacing=(12,12))
# Create the initial series of data
x = linspace(-5, 15.0, 100)
pd = ArrayPlotData(index = x)
# Plot some bessel functions and add the plots to our container
for i in range(9):
pd.set_data("y" + str(i), jn(i,x))
plot = Plot(pd)
plot.plot(("index", "y" + str(i)),
color=tuple(COLOR_PALETTE[i]), line_width=2.0,
bgcolor = "white", border_visible=True)
# Tweak some of the plot properties
plot.border_width = 1
plot.padding = 10
# Set each plot's aspect ratio based on its position in the
# 3x3 grid of plots.
n,m = divmod(i, 3)
plot.aspect_ratio = float(n+1) / (m+1)
# Attach some tools to the plot
plot.tools.append(PanTool(plot))
zoom = ZoomTool(plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
# Add to the grid container
container.add(plot)
return container
def _traj_plot_default(self):
"""Trajectory plot based on TrajectoryView.t_plot in chaco_threading_demo"""
zero = numpy.array([0], 'd')
data = ArrayPlotData(x=zero, y=zero)
h, w = self.traj.Map.H, self.traj.Map.W
data.set_data('x0', zero + self.traj.Map.x0[0])
data.set_data('y0', zero + self.traj.Map.x0[1])
p = Plot(data)
p.plot(('x', 'y'), name='trail', color='red')
p.plot(('x0', 'y0'), name='head', type='scatter', marker='circle', color='red')
p.y_axis.visible = p.x_axis.visible = False
p.y_grid.visible = p.x_grid.visible = False
p.border_visible = True
p.border_width = 2
p.title = 'Rat Trajectory'
p.index_range.set_bounds(0, w)
p.value_range.set_bounds(0, h)
p.overlays.append(PlotLabel('X (%d cm)'%w, component=p, overlay_position='bottom'))
p.overlays.append(PlotLabel('Y (%d cm)'%h, component=p, overlay_position='left', angle=90))
return p
def _plot_default(self):
outcomes, results, time = self._prepare_data()
self.outcomes = outcomes
self.time = time
self.low = int(np.min(time))
self.high = int(np.max(time))
self.data = {}
for outcome in outcomes:
self.data[outcome] = results[outcome]
# Create some data
pd = ArrayPlotData()
for entry in outcomes:
if self.startValue == 'low':
pd.set_data(entry, self.data[entry][:,0])
elif self.startValue == 'high':
pd.set_data(entry, self.data[entry][:,-1])
self.plotdata = pd
# outcomes = outcomes[0:3]
container = GridContainer(shape=(len(outcomes),len(outcomes)))
combis = [(field1, field2) for field1 in outcomes for field2 in outcomes]
selectorTools = []
for entry1, entry2 in combis:
# Create the plot
if entry1 == entry2:
plot = Plot(pd)
else:
plot = Plot(pd)
#set limits for x and y to global limits
plot.range2d._xrange._high_setting = np.max(self.data[entry1])
plot.range2d._xrange._high_value = np.max(self.data[entry1])
plot.range2d._xrange._low_setting = np.min(self.data[entry1])
plot.range2d._xrange._low_value = np.min(self.data[entry1])
plot.range2d._yrange._high_setting =np.max(self.data[entry2])
plot.range2d._yrange._high_value = np.max(self.data[entry2])
plot.range2d._yrange._low_setting = np.min(self.data[entry2])
plot.range2d._yrange._low_value = np.min(self.data[entry2])
#make the scatter plot
plot.plot((entry1, entry2),
type="scatter",
marker="circle",
color="blue",
marker_size=3,
bgcolor="white")[0]
tool = ScatterSelectorTool(component=plot)
tool._index = entry1
plot.tools.append(tool)
selectorTools.append(tool)
plot.height = 500
plot.width = 500
plot.border_width = 1
plot.aspect_ratio = 1.
container.add(plot)
for tool in selectorTools:
tool._other_selectors = list(set(selectorTools) - set([tool]))
tool._demo = self
return container
